Roberto Veraldi (Magna Graecia University of Catanzaro, Italy)
Amerigo Giudice (Magna Graecia University of Catanzaro, Italy)
Paolo Zaffino (Magna Graecia University of Catanzaro, Italy)
Maria Francesca Spadea (Karlsruhe Institute of Technology, Germany)
Project Description
The classification of third molar extraction is a key factor in oral surgery. Developing a deep learning model to classify the difficulty score of extraction would be useful for surgeons and dentists.
This project aims to create a Slicer module that allows clinicians to obtain an extraction-difficulty grade by providing just the patient CT.
Objective
To expose an already developed deep learning classifier in Slicer.
Approach and Plan
Identification of optimal classification parameters
Draft Status
Ready - team will start page creating immediately
Category
Segmentation / Classification / Landmarking
Presenter Location
In-person
Key Investigators
Project Description
The classification of third molar extraction is a key factor in oral surgery. Developing a deep learning model to classify the difficulty score of extraction would be useful for surgeons and dentists. This project aims to create a Slicer module that allows clinicians to obtain an extraction-difficulty grade by providing just the patient CT.
Objective
To expose an already developed deep learning classifier in Slicer.
Approach and Plan
Progress and Next Steps
Illustrations
No response
Background and References
No response